Course Description

An introduction to the concepts of 2D and 3D computer vision. Topics
include: low-level image processing methods such as filtering and edge
detection; segmentation and clustering; optical flow and tracking; shape
reconstruction from stereo, motion, texture, and shading; classification
and recognition. Throughout the course, we also look at aspects of human
vision and perception that guide and inspire computer vision techniques.

Prerequisites:
Prerequisites for the course are COS 217 and COS 226. The course will
require programming (in C, C++, and/or Matlab), as well as some background
in data structures and linear algebra. Experience with signal processing,
statistics, and/or computer graphics is useful but not necessary.

Grading:
There will be four programming assignments worth a total of 70% of the
final grade, as well as a final project worth 30%.

Meeting time/place

TTh 3:00-4:20, CS Building, room 105 (small auditorium)

Questions

We will be using piazza
for Q&A. Please post your questions there instead of mailing the Professor or
TAs, if at all possible.